我想使用tf.with_dependencies函数来保存我的RNN状态。出于某种原因，我收到以下错误。
Traceback (most recent call last):
File "/home/chase/workspace/AudioRNN/audiornn.py", line 56, in <module>
tf.with_dependencies([expected_output], input_tensor)
AttributeError: module 'tensorflow' has no attribute 'with_dependencies'
我的tensorflow代码的其余部分运行正常。我在eclipse中，我按Ctrl +单击tf.with_dependencies，它将我带到源代码。我注意到tf.group函数也在这个文件中，我可以称之为正常。 tf.with_dependencies有什么问题？我在Ubuntu 16.04上。我正在使用python 3和tensorflow的最新版本。
根据要求，这是dir(tf)的打印件。
AggregationMethod
Assert
AttrValue
ConfigProto
DType
DeviceSpec
Dimension
Event
FIFOQueue
FixedLenFeature
FixedLenSequenceFeature
FixedLengthRecordReader
GPUOptions
GRAPH_DEF_VERSION
GRAPH_DEF_VERSION_MIN_CONSUMER
GRAPH_DEF_VERSION_MIN_PRODUCER
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IdentityReader
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Print
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Summary
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Tensor
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zeta
答案 0 :(得分：5)
TensorFlow API中没有这样的功能。相反，您可以使用with tf.control_dependencies():和tf.identity()来达到预期的效果：
with tf.control_dependencies([expected_output]):
result = tf.identity(input_tensor)
答案 1 :(得分：1)
或尝试： 来自tensorflow.python.ops.control_flow_ops导入with_dependencies
答案 2 :(得分：0)
tf.with_dependencies在2015年底某个地方已弃用。尽管如此，它仍在tf代码it is no longer exported中定义（函数前面没有@tf_export），因此不可用
使用
with tf.control_dependencies([expected_output]):
result = tf.identity(input_tensor)
正如mrry所建议的，因为它的作用完全相同。